Search results for: niche fitness evaluation model

Authors: Ahmed AlNouss, Salim Ahmed

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Process control refers to the techniques to control the variables in a process in order to maintain them at their desired values. Advanced process control (APC) is a broad term within the domain of control where it refers to different kinds of process control and control related tools, for example, model predictive control (MPC), statistical process control (SPC), fault detection and classification (FDC) and performance assessment. APC is often used for solving multivariable control problems and model predictive control (MPC) is one of only a few advanced control methods used successfully in industrial control applications. Advanced control is expected to bring many benefits to the plant operation; however, the extent of the benefits is plant specific and the application needs a large investment. This requires an analysis of the expected benefits before the implementation of the control. In a real plant simulation studies are carried out along with some experimentation to determine the improvement in the performance of the plant due to advanced control. In this research, such an exercise is undertaken to realize the needs of APC application. The main objectives of the paper are as follows: (1) To apply MPC to a number of simulations set up to realize the need of MPC by comparing its performance with that of proportional integral derivatives (PID) controllers. (2) To study the effect of controller parameters on control performance. (3) To develop appropriate performance index (PI) to compare the performance of different controller and develop novel idea to present tuning map of a controller. These objectives were achieved by applying PID controller and a special type of MPC which is dynamic matrix control (DMC) on the multi-tanks process simulated in loop-pro. Then the controller performance has been evaluated by changing the controller parameters. This performance was based on special indices related to the difference between set point and process variable in order to compare the both controllers. The same principle was applied for continuous stirred tank heater (CSTH) and continuous stirred tank reactor (CSTR) processes simulated in Matlab. However, in these processes some developed programs were written to evaluate the performance of the PID and MPC controllers. Finally these performance indices along with their controller parameters were plotted using special program called Sigmaplot. As a result, the improvement in the performance of the control loops was quantified using relevant indices to justify the need and importance of advanced process control. Also, it has been approved that, by using appropriate indices, predictive controller can improve the performance of the control loop significantly.

Keywords: advanced process control (APC), control loop, model predictive control (MPC), proportional integral derivatives (PID), performance indices (PI)

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Authors: Bo Jin

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A variety of process equipment having flow in and out is widely used in industrial land-based cryogenic facilities. In some of this equipment, such as vapor-liquid separator, a liquid level is established during the steady operation. As the implementation of such industrial processes extends to off-shore floating facilities, it is important to investigate the effect of sea motion on the process equipment partially filled with liquid. One important aspect to consider is the occurrence of sloshing therein. The flow characteristics are different from the classical study of sloshing, where the fluid is enclosed inside a vessel (e.g., storage tank) with no flow in or out. Liquid inside process equipment continuously flows in and out of the system. To understand this key difference, a Computational Fluid Dynamics (CFD) model is developed to simulate the liquid motion inside a partially filled cylinder with and without continuous flow in and out. For a partially filled vertical cylinder without any continuous flow in and out, the CFD model is found to be able to capture the well-known sloshing behavior documented in the literature. For the cylinder with a continuous steady flow in and out, the CFD simulation results demonstrate that the continuous flow suppresses sloshing. Given typical cryogenic fluid has very low viscosity, an analysis based on potential flow theory is developed to explain why flow into and out of the cylinder changes the natural frequency of the system and thereby suppresses sloshing. This analysis further validates the CFD results.

Keywords: computational fluid dynamics, CFD, cryogenic process equipment, off-shore floating processes, sloshing

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Authors: Granny K. Lobega, Ntsako Idrs Makamu

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The envisaged paper was to evaluate the implementation of training and development in a South African Municipality. The paper adopted a qualitative research approach. Primary data were collected from 20 participants which were sampled from the municipality, and data were collected by using semi-structured interviews. The main objective of the study was to assess the reason for the implementation of training and development program by the municipality. The study revealed that workers are helped to focus, and priority is placed on empowering employees, productivity is increased and contributing to better team morale. The study recommended that the municipality must establish proper procedures to be followed when selecting qualifying employees to attend the training and further use the training audit to establish the necessary training to be offered to qualifying employees.

Keywords: training, development, municipality, evaluation, human resource management

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Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

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This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

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Authors: Yilei Song, Linlin Tian, Ning Zhao

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Turbulence energetics and structures in the wake of large-scale wind turbines under the stably-stratified atmospheric boundary layer (SABL) can be complicated due to the presence of low-level jets (LLJs), a region of higher wind speeds than the geostrophic wind speed. With a modified one-k-equation, eddy viscosity model specified for atmospheric flows as the sub-grid scale (SGS) model, a realistic atmospheric state of the stable ABL is well reproduced by large-eddy simulation (LES) techniques. Corresponding to the precursor stably stratification, the detailed wake properties of a standard 5-MW wind turbine represented as an actuator line model are provided. An engineering model is proposed for wake prediction based on the simulation statistics and gets validated. Results confirm that the proposed wake model can provide good predictions for wind turbines under the SABL.

Keywords: large-eddy simulation, stably-stratified atmospheric boundary layer, wake model, wind turbine wake

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Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

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Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Y. Smirlis, G. Koronakos, S. Plitsos

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Shipbrokers assist the ship companies in chartering or selling and buying vessels, acting as intermediates between them and the market. They facilitate deals, providing their expertise, negotiating skills, and knowledge about ship market bargains. Their role is very important as it affects the profitability and market position of a shipping company. Due to their significant contribution, the shipping companies have to employ systematic procedures to evaluate the shipbrokers’ services in order to select the best and, consequently, to achieve the best deals. Towards this, in this paper, we consider shipbrokers as financial service providers, and we formulate the problem of evaluating and selecting shipbrokers’ services as a multi-criteria decision making (MCDM) procedure. The proposed methodology comprises a first normalization step to adjust different scales and orientations of the criteria and a second step that includes the mathematical model to evaluate the performance of the shipbrokers’ services involved in the assessment. The criteria along which the shipbrokers are assessed may refer to their size and reputation, the potential efficiency of the services, the terms and conditions imposed, the expenses (e.g., commission – brokerage), the expected time to accomplish a chartering or selling/buying task, etc. and according to our modelling approach these criteria may be assigned different importance. The mathematical programming model performs a comparative assessment and estimates for the shipbrokers involved in the evaluation, a relative score that ranks the shipbrokers in terms of their potential performance. To illustrate the proposed methodology, we present a case study in which a shipping company evaluates and selects the most suitable among a number of sale and purchase (S&P) brokers. Acknowledgment: This study is supported by the OptiShip project, implemented within the framework of the National Recovery Plan and Resilience “Greece 2.0” and funded by the European Union – NextGenerationEU programme.

Keywords: shipbrokers, multi-criteria decision making, mathematical programming, service-provider selection

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Authors: M. J. Kang, Y. N. Jo, H. H. Yoo

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Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.

Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex

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Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

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Authors: Y. S. Yusoff, G. Streftaris, H. R Waters

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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease

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Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González

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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.

Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

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Authors: Milena Serzante, Viktoriia Stankevich, Yousre Badir

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Companies have a significant impact on the environment and society, and sustainability is important not only for ethical concerns but also for financial and economic reasons. The aim of the study is to analyze how the sustainable performance of the company impacts the economy and the business's economic performance. To achieve this goal, such methods as the Pearson correlation, Multiple Linear Regression, Cook's distance method, K-nearest neighbor and COPRAS technique were implemented. The results revealed that there is no significant correlation between different indicators of sustainable development of the company and both GDP and Return on Equity. It indicates that the methodology of evaluating sustainability causes the difference in ranking companies based on sustainable performance.

Keywords: economic impact, sustainability evaluation, sustainable companies, economic indicators, sustainability, GDP, return on equity

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Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

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Authors: Fatma Ülkü Kavruk

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The comparison of the old and new approaches reveals that the concept of equivalence has been interpreted and categorized in different ways by different scholars throughout the history. The aim of this study is to trace the concept of equivalence in translation theories from the linguistics-oriented era to present, referring to various translation scholars and to provide a critical evaluation of the nature and applicability of the concept of equivalence in today’s world of translation studies. Within the study, various interpretations of equivalence proposed by international scholars in translation studies are to be presented. In order to find out the reflections of these scholars’ approaches to the Turkish scholars’ research, the interpretations of equivalence by various Turkish scholars are to be examined. At the end of the paper, the applicability of the concept of equivalence in real life is to be discussed in light of these approaches.

Keywords: translation studies, equivalence, translation theories, evaluation

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Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: genetic algorithm, rsm, biodiesel, karanja

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

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Authors: F. S. Kadhim, A. Samsuri, H. Alwan

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Well logging records can help to answer many questions from a wide range of special interested information and basic petrophysical properties to formation evaluation of oil and gas reservoirs. The accurate calculations of porosity in carbonate reservoirs are the most challenging aspects of well log analysis. Many equations have been developed over the years based on known physical principles or on empirically derived relationships, which are used to calculate porosity, estimate lithology and water saturation; however these parameters are calculated from well logs by using modern technique in a current study. Nasiriya (NS) oilfield is one of giant oilfields in the Middle East, and the formation under study is the Mishrif carbonate formation which is the shallowest hydrocarbon bearing zone in the NS oilfield. Neurolog software (V5, 2008) was used to digitize the scanned copies of the available logs. Environmental corrections had been made as per Schlumberger charts 2005, which supplied in the Interactive Petrophysics software (IP, V3.5, 2008). Three saturation models have been used to calculate water saturation of carbonate formations, which are simple Archie equation, Dual water model, and Indonesia model. Results indicate that the Mishrif formation consists mainly of limestone, some dolomite and shale. The porosity interpretation shows that the logging tools have a good quality after making the environmental corrections. The average formation water saturation for Mishrif formation is around 0.4-0.6.This study is provided accurate behavior of petrophysical properties with depth for this formation by using modern software.

Keywords: lithology, porosity, water saturation, carbonate formation, mishrif formation

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Authors: Mehtap Dursun, Zeynep Şener

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Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar

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With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.

Keywords: home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Sadife Güngör, Sevilay Konya, Zeynep Karaçor

Abstract:

Inflation and foreign trade are the most important economic indicator of a country. In this study, Turkey's economy with the policies adopted after 2000, given how performs an economic transformation. This transformation of the economy is discussed with inflation and foreign trade. In this context, attention is drawn to 2001 Strong Economy and Transition Program and 2006 Inflation Targeting Regime. The evaluation was performed of after the year 2000 inflation and foreign trade figures in Turkey economy. When we looked the progress, after 2000 in Turkey economy, we can say a new process was built up.

Keywords: inflation, foreign trade, 2001 strong economy programme, 2006 inflation targeting regime

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